actual comparison across audio/video numerically
summary(sixseven_basiclevel_home_data_agg)
## subj month SubjectNumber audio_video numspeakers
## 01 : 4 06:87 01_06 : 2 audio:88 Min. : 1.000
## 02 : 4 07:88 01_07 : 2 video:87 1st Qu.: 3.000
## 03 : 4 02_06 : 2 Median : 4.000
## 04 : 4 02_07 : 2 Mean : 4.909
## 06 : 4 03_06 : 2 3rd Qu.: 6.000
## 07 : 4 03_07 : 2 Max. :16.000
## (Other):151 (Other):163
## numtokens numtypes FAT MOT
## Min. : 11.0 Min. : 6.0 Min. : 0.00 Min. : 0
## 1st Qu.: 141.0 1st Qu.: 50.5 1st Qu.: 0.00 1st Qu.: 98
## Median : 299.0 Median :103.0 Median : 8.00 Median : 205
## Mean : 442.1 Mean :121.3 Mean : 61.15 Mean : 276
## 3rd Qu.: 677.0 3rd Qu.:186.0 3rd Qu.: 71.50 3rd Qu.: 381
## Max. :1791.0 Max. :379.0 Max. :768.00 Max. :1486
##
## num_exp_tokens num_exp_types d q
## Min. : 0.00 Min. : 0.000 Min. : 5.0 Min. : 0.00
## 1st Qu.: 22.00 1st Qu.: 6.500 1st Qu.: 57.0 1st Qu.: 32.50
## Median : 57.00 Median :10.000 Median :130.0 Median : 69.00
## Mean : 81.33 Mean : 9.863 Mean :206.6 Mean : 89.48
## 3rd Qu.:113.50 3rd Qu.:13.000 3rd Qu.:307.5 3rd Qu.:118.00
## Max. :335.00 Max. :17.000 Max. :879.0 Max. :469.00
##
## s r n i
## Min. : 0.00 Min. : 0.00 Min. : 0.00 Min. : 0.00
## 1st Qu.: 3.00 1st Qu.: 0.00 1st Qu.: 9.50 1st Qu.: 7.50
## Median : 15.00 Median : 10.00 Median : 27.00 Median : 19.00
## Mean : 44.61 Mean : 36.19 Mean : 38.36 Mean : 26.82
## 3rd Qu.: 41.00 3rd Qu.: 42.00 3rd Qu.: 51.00 3rd Qu.: 37.00
## Max. :564.00 Max. :256.00 Max. :219.00 Max. :173.00
##
## TOY n_op y_op prop_op
## Min. : 0.00 Min. : 7.0 Min. : 3.0 Min. :0.1053
## 1st Qu.: 0.00 1st Qu.: 56.5 1st Qu.: 70.0 1st Qu.:0.3860
## Median : 0.00 Median : 122.0 Median : 145.0 Median :0.5240
## Mean : 14.23 Mean : 214.9 Mean : 226.3 Mean :0.5277
## 3rd Qu.: 12.50 3rd Qu.: 327.0 3rd Qu.: 318.5 3rd Qu.:0.6782
## Max. :383.00 Max. :1096.0 Max. :1046.0 Max. :0.8992
##
## n_op_exp y_op_exp prop_op_exp CHI
## Min. : 0.00 Min. : 0.00 Min. :0.0000 Min. :0
## 1st Qu.: 8.50 1st Qu.: 13.00 1st Qu.:0.4356 1st Qu.:0
## Median : 23.00 Median : 30.00 Median :0.5753 Median :0
## Mean : 33.99 Mean : 47.24 Mean :0.5535 Mean :0
## 3rd Qu.: 51.00 3rd Qu.: 66.00 3rd Qu.:0.7040 3rd Qu.:0
## Max. :175.00 Max. :264.00 Max. :0.9524 Max. :0
##
## CHItypes prop_mom prop_dad prop_parent
## Min. :0 Min. :0.0000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0 1st Qu.:0.4961 1st Qu.:0.00000 1st Qu.:0.7163
## Median :0 Median :0.7377 Median :0.02222 Median :0.8746
## Mean :0 Mean :0.6581 Mean :0.13062 Mean :0.7887
## 3rd Qu.:0 3rd Qu.:0.8807 3rd Qu.:0.17247 3rd Qu.:0.9719
## Max. :0 Max. :1.0000 Max. :1.00000 Max. :1.0000
##
## prop_tech tech propd propi
## Min. :0.000000 Min. : 0.00 Min. :0.07092 Min. :0.00000
## 1st Qu.:0.000000 1st Qu.: 0.00 1st Qu.:0.36767 1st Qu.:0.03149
## Median :0.007463 Median : 2.00 Median :0.46746 Median :0.05847
## Mean :0.048776 Mean : 26.46 Mean :0.45019 Mean :0.06651
## 3rd Qu.:0.052437 3rd Qu.: 18.50 3rd Qu.:0.54669 3rd Qu.:0.08723
## Max. :0.602837 Max. :472.00 Max. :0.73485 Max. :0.22436
##
## propn propq propr props
## Min. :0.00000 Min. :0.0000 Min. :0.00000 Min. :0.000000
## 1st Qu.:0.04956 1st Qu.:0.1683 1st Qu.:0.00000 1st Qu.:0.009472
## Median :0.08065 Median :0.2143 Median :0.02739 Median :0.035000
## Mean :0.09466 Mean :0.2282 Mean :0.06887 Mean :0.091467
## 3rd Qu.:0.11601 3rd Qu.:0.2793 3rd Qu.:0.10614 3rd Qu.:0.120044
## Max. :0.52941 Max. :0.5870 Max. :0.56647 Max. :0.808511
##
## type_token_ratio exp_type_ratio exp_token_ratio ent_subj_av
## Min. :0.1435 Min. :0.00000 Min. :0.0000 Min. :1.039
## 1st Qu.:0.2644 1st Qu.:0.06760 1st Qu.:0.1425 1st Qu.:1.700
## Median :0.3289 Median :0.09244 Median :0.1782 Median :1.901
## Mean :0.3297 Mean :0.10721 Mean :0.1850 Mean :1.875
## 3rd Qu.:0.3857 3rd Qu.:0.13423 3rd Qu.:0.2252 3rd Qu.:2.048
## Max. :0.6441 Max. :0.38462 Max. :0.4824 Max. :2.529
##
## sum_prop_ut noun_chi_onset posttalk
## Min. :0.9900 Min. : 8.00 Mode :logical
## 1st Qu.:1.0000 1st Qu.:10.00 FALSE:175
## Median :1.0000 Median :12.00 NA's :0
## Mean :0.9999 Mean :12.04
## 3rd Qu.:1.0000 3rd Qu.:14.00
## Max. :1.0000 Max. :17.00
## NA's :8
sixseven_basiclevel_home_data_agg%>%
filter(subj!="17")%>%#missing a recording
summarise_each(funs(wilcox.test(.[audio_video == "audio"], .[audio_video == "video"])$p.value,
cor.test(.[audio_video == "audio"], .[audio_video == "video"], method = "spearman")$p.value,
cor.test(.[audio_video == "audio"], .[audio_video == "video"], method = "spearman")$estimate),
#cor.test(.[audio_video == "audio"], .[audio_video == "video"], method = "spearman")$estimate),
vars = numspeakers:ent_subj_av)
## Warning in cor.test.default(c(4, 3, 5, 2, 7, 2, 7, 1, 4, 2, 6, 3, 12, 5, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(440, 120, 532, 114, 873, 58, 743, 49, 606, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(125, 62, 182, 31, 260, 26, 203, 24, 269,
## 29, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(89, 7, 195, 0, 69, 0, 3, 0, 47, 0, 44, 0, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(327, 112, 317, 111, 701, 56, 542, 49, 495, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(154, 9, 66, 16, 134, 9, 158, 5, 71, 6, 78, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(12, 6, 14, 6, 15, 4, 14, 2, 13, 3, 12, 4, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(176, 47, 282, 26, 446, 29, 361, 19, 233,
## 23, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(64, 28, 79, 18, 188, 26, 148, 27, 88, 19, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(28, 2, 92, 68, 41, 0, 91, 0, 12, 6, 13, 0, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(67, 29, 0, 0, 116, 0, 79, 0, 220, 0, 86,
## 15, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(84, 13, 57, 0, 42, 2, 24, 0, 36, 5, 32, 21, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(21, 1, 22, 2, 40, 1, 40, 3, 17, 1, 16, 4, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0, 0, 0, 0, 0, 0, 17, 0, 0, 0, 0, 4, 383, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(189, 53, 328, 35, 381, 25, 277, 19, 284,
## 21, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(251, 67, 185, 79, 481, 33, 401, 30, 322,
## 33, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.570454545454545, 0.558333333333333,
## 0.360623781676413, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(57, 6, 37, 3, 49, 1, 39, 1, 37, 5, 14, 3, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(97, 3, 28, 13, 85, 8, 106, 4, 34, 1, 62,
## 33, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.62987012987013, 0.333333333333333,
## 0.430769230769231, : Cannot compute exact p-value with ties
## Warning in cor(rank(x), rank(y)): the standard deviation is zero
## Warning in cor(rank(x), rank(y)): the standard deviation is zero
## Warning in cor.test.default(c(0.743181818181818, 0.933333333333333,
## 0.595864661654135, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.202272727272727, 0.0583333333333333,
## 0.366541353383459, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.945454545454545, 0.991666666666667,
## 0.962406015037594, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0, 0, 0, 0, 0, 0, 0.0228802153432032, 0,
## 0.0066006600660066, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0, 0, 0, 0, 0, 0, 17, 0, 4, 0, 0, 4, 390, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.4, 0.391666666666667, 0.530075187969925, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.0477272727272727, 0.00833333333333333,
## 0.0413533834586466, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.190909090909091, 0.108333333333333,
## 0.107142857142857, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.145454545454545, 0.233333333333333,
## 0.148496240601504, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.152272727272727, 0.241666666666667, 0, 0, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.0636363636363636, 0.0166666666666667,
## 0.172932330827068, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.284090909090909, 0.516666666666667,
## 0.342105263157895, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.096, 0.0967741935483871,
## 0.0769230769230769, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(4, 3, 5, 2, 7, 2, 7, 1, 4, 2, 6, 3, 12, 5, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(440, 120, 532, 114, 873, 58, 743, 49, 606, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(125, 62, 182, 31, 260, 26, 203, 24, 269,
## 29, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(89, 7, 195, 0, 69, 0, 3, 0, 47, 0, 44, 0, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(327, 112, 317, 111, 701, 56, 542, 49, 495, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(154, 9, 66, 16, 134, 9, 158, 5, 71, 6, 78, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(12, 6, 14, 6, 15, 4, 14, 2, 13, 3, 12, 4, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(176, 47, 282, 26, 446, 29, 361, 19, 233,
## 23, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(64, 28, 79, 18, 188, 26, 148, 27, 88, 19, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(28, 2, 92, 68, 41, 0, 91, 0, 12, 6, 13, 0, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(67, 29, 0, 0, 116, 0, 79, 0, 220, 0, 86,
## 15, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(84, 13, 57, 0, 42, 2, 24, 0, 36, 5, 32, 21, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(21, 1, 22, 2, 40, 1, 40, 3, 17, 1, 16, 4, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0, 0, 0, 0, 0, 0, 17, 0, 0, 0, 0, 4, 383, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(189, 53, 328, 35, 381, 25, 277, 19, 284,
## 21, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(251, 67, 185, 79, 481, 33, 401, 30, 322,
## 33, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.570454545454545, 0.558333333333333,
## 0.360623781676413, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(57, 6, 37, 3, 49, 1, 39, 1, 37, 5, 14, 3, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(97, 3, 28, 13, 85, 8, 106, 4, 34, 1, 62,
## 33, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.62987012987013, 0.333333333333333,
## 0.430769230769231, : Cannot compute exact p-value with ties
## Warning in cor(rank(x), rank(y)): the standard deviation is zero
## Warning in cor(rank(x), rank(y)): the standard deviation is zero
## Warning in cor.test.default(c(0.743181818181818, 0.933333333333333,
## 0.595864661654135, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.202272727272727, 0.0583333333333333,
## 0.366541353383459, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.945454545454545, 0.991666666666667,
## 0.962406015037594, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0, 0, 0, 0, 0, 0, 0.0228802153432032, 0,
## 0.0066006600660066, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0, 0, 0, 0, 0, 0, 17, 0, 4, 0, 0, 4, 390, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.4, 0.391666666666667, 0.530075187969925, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.0477272727272727, 0.00833333333333333,
## 0.0413533834586466, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.190909090909091, 0.108333333333333,
## 0.107142857142857, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.145454545454545, 0.233333333333333,
## 0.148496240601504, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.152272727272727, 0.241666666666667, 0, 0, :
## Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.0636363636363636, 0.0166666666666667,
## 0.172932330827068, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.284090909090909, 0.516666666666667,
## 0.342105263157895, : Cannot compute exact p-value with ties
## Warning in cor.test.default(c(0.096, 0.0967741935483871,
## 0.0769230769230769, : Cannot compute exact p-value with ties
## # A tibble: 1 x 37
## `vars1_$` `vars2_$` `vars3_$` `vars4_$` `vars5_$` `vars6_$` `vars7_$`
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 0.1794435 0.4897253 0.4419861 0.3550851 0.4923028 0.4470059 0.4089341
## # ... with 30 more variables: `vars8_$` <dbl>, `vars9_$` <dbl>,
## # `vars10_$` <dbl>, `vars11_$` <dbl>, `vars12_$` <dbl>,
## # `vars13_$` <dbl>, `vars14_$` <dbl>, `vars15_$` <dbl>,
## # `vars16_$` <dbl>, `vars17_$` <dbl>, `vars18_$` <dbl>,
## # `vars19_$` <dbl>, `vars20_$` <dbl>, `vars21_$` <dbl>,
## # `vars22_$` <dbl>, `vars23_$` <dbl>, `vars24_$` <dbl>,
## # `vars25_$` <dbl>, `vars26_$` <dbl>, `vars27_$` <dbl>,
## # `vars28_$` <dbl>, `vars29_$` <dbl>, `vars30_$` <dbl>,
## # `vars31_$` <dbl>, `vars32_$` <dbl>, `vars33_$` <dbl>,
## # `vars34_$` <dbl>, `vars35_$` <dbl>, `vars36_$` <dbl>, `vars37_$` <dbl>
#View(sixseven_basiclevel_home_data_agg)
stats
#need to redo as moving window
lm_quant_prop <- lm(data = sixseven_basiclevel_home_data_agg, type_token_ratio ~ month + audio_video)
anova(lm_quant_prop)
## Analysis of Variance Table
##
## Response: type_token_ratio
## Df Sum Sq Mean Sq F value Pr(>F)
## month 1 0.00088 0.000884 0.1269 0.7221
## audio_video 1 0.27410 0.274099 39.3400 2.788e-09 ***
## Residuals 172 1.19840 0.006967
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
plot(lm_quant_prop)




summary(lm_quant_prop)
##
## Call:
## lm(formula = type_token_ratio ~ month + audio_video, data = sixseven_basiclevel_home_data_agg)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.184288 -0.058783 -0.008734 0.049558 0.277039
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.292825 0.010908 26.844 < 2e-16 ***
## month07 -0.004951 0.012620 -0.392 0.695
## audio_videovideo 0.079155 0.012620 6.272 2.79e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.08347 on 172 degrees of freedom
## Multiple R-squared: 0.1866, Adjusted R-squared: 0.1772
## F-statistic: 19.73 on 2 and 172 DF, p-value: 1.926e-08
sixseven_basiclevel_home_data_agg %>%
group_by(month, audio_video)%>%
summarise(mean(type_token_ratio))
## Source: local data frame [4 x 3]
## Groups: month [?]
##
## # A tibble: 4 x 3
## month audio_video `mean(type_token_ratio)`
## <fctr> <fctr> <dbl>
## 1 06 audio 0.2903638
## 2 06 video 0.3744989
## 3 07 audio 0.2903356
## 4 07 video 0.3645678
#sixseven_spreadAV %>%
sixseven_basiclevel_home_data_agg %>%
group_by(month, audio_video)%>%
summarise(median(numspeakers, na.rm=T),
mean(numspeakers, na.rm=T),
sd(numspeakers, na.rm=T))
## Source: local data frame [4 x 5]
## Groups: month [?]
##
## # A tibble: 4 x 5
## month audio_video `median(numspeakers, na.rm = T)`
## <fctr> <fctr> <dbl>
## 1 06 audio 5
## 2 06 video 3
## 3 07 audio 7
## 4 07 video 3
## # ... with 2 more variables: `mean(numspeakers, na.rm = T)` <dbl>,
## # `sd(numspeakers, na.rm = T)` <dbl>
sixseven_basiclevel_home_data_agg %>%
group_by(month, audio_video)%>%
summarise(median(FAT, na.rm=T),
mean(FAT, na.rm=T),
sd(FAT, na.rm=T))
## Source: local data frame [4 x 5]
## Groups: month [?]
##
## # A tibble: 4 x 5
## month audio_video `median(FAT, na.rm = T)` `mean(FAT, na.rm = T)`
## <fctr> <fctr> <dbl> <dbl>
## 1 06 audio 67.0 103.250000
## 2 06 video 0.0 15.837209
## 3 07 audio 40.5 115.431818
## 4 07 video 0.0 9.045455
## # ... with 1 more variables: `sd(FAT, na.rm = T)` <dbl>
# none of the audio differences 6 vs 7 are different
wa1 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$numtokens,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$numtokens, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
wa2 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$numtypes,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$numtypes, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
wa3 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$numspeakers,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$numspeakers, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
wa4 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$MOT,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$MOT, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
wa5 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$FAT,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$FAT, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
wa6 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$d,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$d, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
wa7 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$q,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$q, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
wa8 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$r,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$r, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
wa9 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$i,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$i, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
wa10 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$n,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$n, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
wa11 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$s,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$s, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
wa12 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$y_op,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$n_op, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
#most video 6vs7 aren't different
wv1 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$numtokens,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$numtokens, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
wv2 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$numtypes,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$numtypes, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
wv3 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$numspeakers,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$numspeakers, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
wv4 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$MOT,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$MOT, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
wv5 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$d,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$d, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
wv6 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$r,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$r, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
wv7 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$i,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$i, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
wv8 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$y_op,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$y_op, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
wv9 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$q,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$q, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
wv10 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$n,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$n, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
wv11 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$s,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$s, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
wv12 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06" & subj!="17")$FAT,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07" & subj!="17")$FAT, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with ties
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
# none of the audio differences 6 vs 7 are different
ca1 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$numtokens,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$numtokens, conf.int=T, method = "kendall")
ca2 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$numtypes,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$numtypes, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
ca3 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$numspeakers,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$numspeakers, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
ca4 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$MOT,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$MOT, conf.int=T, method = "kendall")
ca5 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$FAT,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$FAT, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
ca6 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$d,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$d, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
ca7 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$q,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$q, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
ca8 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$r,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$r, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
ca9 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$i,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$i, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
ca10 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$n,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$n, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
ca11 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$s,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$s, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
ca12 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$y_op,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$n_op, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
#most video 6vs7 aren't different
cv1 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$numtokens,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$numtokens, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
cv2 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$numtypes,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$numtypes, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
cv3 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$numspeakers,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$numspeakers, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
cv4 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$MOT,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$MOT, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
cv5 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$d,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$d, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
cv6 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$r,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$r, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
cv7 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$i,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$i, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
cv8 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$y_op,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$y_op, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
cv9 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$q,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$q, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
cv10 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$n,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$n, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
cv11 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$s,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$s, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
cv12 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06" & subj!="17")$FAT,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07" & subj!="17")$FAT, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
cv_ps <- cbind(cv1$p.value,cv2$p.value,cv3$p.value, cv4$p.value, cv5$p.value, cv6$p.value, cv7$p.value, cv8$p.value, cv9$p.value, cv10$p.value, cv11$p.value, cv12$p.value)
round(p.adjust(cv_ps, method = "holm"),3)
## [1] 0.000 0.000 0.014 0.000 0.000 0.066 0.004 0.001 0.000 0.001 0.024
## [12] 0.000
round(cv_ps,3)
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
## [1,] 0 0 0.005 0 0 0.066 0.001 0 0 0 0.012 0
table(cv_ps<.05)
##
## FALSE TRUE
## 1 11
table(p.adjust(cv_ps, method = "holm")<.05)
##
## FALSE TRUE
## 1 11
cv6
##
## Kendall's rank correlation tau
##
## data: subset(sixseven_basiclevel_home_data_agg, audio_video == "video" & and subset(sixseven_basiclevel_home_data_agg, audio_video == "video" & month == "06" & subj != "17")$r and month == "07" & subj != "17")$r
## z = 1.8384, p-value = 0.066
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.229212
#taking out cv7 bc it's not sig, reading count
cv_taus <- cbind(cv1$estimate,cv2$estimate,cv3$estimate, cv4$estimate, cv5$estimate, cv6$estimate, cv8$estimate, cv9$estimate, cv10$estimate, cv11$estimate, cv12$estimate)
range(cv_taus)
## [1] 0.2292120 0.5973362
ca_ps <- cbind(ca1$p.value,ca2$p.value,ca3$p.value, ca4$p.value, ca5$p.value, ca6$p.value, ca7$p.value, ca8$p.value, ca9$p.value, ca10$p.value, ca11$p.value, ca12$p.value)
round(p.adjust(ca_ps, method = "holm"),3)
## [1] 0.001 0.010 0.011 0.000 0.004 0.000 0.000 0.001 0.010 0.015 0.003
## [12] 0.006
round(ca_ps, 3)
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
## [1,] 0 0.002 0.006 0 0.001 0 0 0 0.003 0.015 0 0.001
table(ca_ps<.05)
##
## TRUE
## 12
table(p.adjust(ca_ps, method = "holm")<.05)
##
## TRUE
## 12
wv_ps <- cbind(wv1$p.value,wv2$p.value,wv3$p.value, wv4$p.value, wv5$p.value, wv6$p.value, wv7$p.value, wv8$p.value, wv9$p.value, wv10$p.value, wv11$p.value, wv12$p.value)
round(p.adjust(wv_ps, method = "holm"),3)
## [1] 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 0.420 0.292 0.199
## [12] 0.155
round(wv_ps, 3)
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
## [1,] 0.534 0.62 0.163 0.591 0.249 0.516 0.692 0.557 0.047 0.029 0.018
## [,12]
## [1,] 0.013
table(wv_ps<.05)
##
## FALSE TRUE
## 8 4
table(p.adjust(wv_ps, method = "holm")<.05)
##
## FALSE
## 12
ca_taus <- cbind(ca1$estimate,ca2$estimate,ca3$estimate, ca4$estimate, ca5$estimate, ca6$estimate, ca7$estimate, ca8$estimate, ca9$estimate, ca10$estimate, ca11$estimate, ca12$estimate)
range(ca_taus)
## [1] 0.2565195 0.5137421
wa_ps <- cbind(wa1$p.value,wa2$p.value,wa3$p.value, wa4$p.value, wa5$p.value, wa6$p.value, wa7$p.value, wa8$p.value, wa9$p.value, wa10$p.value, wa11$p.value, wa12$p.value)
round(p.adjust(wa_ps, method = "holm"),3)
## [1] 1 1 1 1 1 1 1 1 1 1 1 1
round(wa_ps, 3)
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
## [1,] 0.875 0.793 0.09 0.649 0.876 0.793 0.283 0.894 0.876 0.744 0.518
## [,12]
## [1,] 0.649
table(wa_ps<.05)
##
## FALSE
## 12
table(p.adjust(wa_ps, method = "holm")<.05)
##
## FALSE
## 12
sixseven_basiclevel_home_data_agg%>%
group_by(audio_video) %>%
summarise(meantokens = mean(numtokens, na.rm=T),
meantokens_hour = mean(as.numeric(as.character(ifelse(audio_video=="audio", numtokens/11, numtokens))), na.rm=T))
## # A tibble: 2 x 3
## audio_video meantokens meantokens_hour
## <fctr> <dbl> <dbl>
## 1 audio 713.6023 64.87293
## 2 video 167.4023 167.40230
# none of the audio differences 6 vs 7 are different
pwa1 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$prop_op,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$prop_op, conf.int=T, paired = T)
pwa2 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$prop_mom,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$prop_mom, conf.int=T, paired = T)
pwa3 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$prop_dad,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$prop_dad, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
pwa4 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$propd,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$propd, conf.int=T, paired = T)
pwa5 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$propi,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$propi, conf.int=T, paired = T)
pwa6 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$propr,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$propr, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
pwa7 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$propq,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$propq, conf.int=T, paired = T)
pwa8 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$props,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$props, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
pwa9 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$propn,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$propn, conf.int=T, paired = T)
pwa10 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$type_token_ratio,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$type_token_ratio, conf.int=T, paired = T)
#most video 6vs7 aren't different
pwv1 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$prop_op,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$prop_op, conf.int=T, paired = T)
pwv2 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$prop_mom,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$prop_mom, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
pwv3 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$prop_dad,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$prop_dad, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
pwv4 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$propd,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$propd, conf.int=T, paired = T)
pwv5 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$propi,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$propi, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
pwv6 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$propr,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$propr, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
pwv7 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$propq,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$propq, conf.int=T, paired = T)
pwv8 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$props,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$props, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
pwv9 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$propn,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$propn, conf.int=T, paired = T)
pwv10 <- wilcox.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$type_token_ratio,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$type_token_ratio, conf.int=T, paired = T)
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(subset(sixseven_basiclevel_home_data_agg, :
## cannot compute exact confidence interval with zeroes
# none of the audio differences 6 vs 7 are different
pca1 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$prop_op,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$prop_op, conf.int=T, method = "kendall")
pca2 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$prop_mom,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$prop_mom, conf.int=T, method = "kendall")
pca3 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$prop_dad,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$prop_dad, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
pca4 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$propd,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$propd, conf.int=T, method = "kendall")
pca5 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$propi,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$propi, conf.int=T, method = "kendall")
pca6 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$propr,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$propr, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
pca7 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$propq,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$propq, conf.int=T, method = "kendall")
pca8 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$props,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$props, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
pca9 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$propn,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$propn, conf.int=T, method = "kendall")
pca10 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="06")$type_token_ratio,
subset(sixseven_basiclevel_home_data_agg, audio_video=="audio" & month=="07")$type_token_ratio, conf.int=T, method = "kendall")
#most video 6vs7 aren't different
pcv1 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$prop_op,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$prop_op, conf.int=T, method = "kendall")
pcv2 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$prop_mom,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$prop_mom, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
pcv3 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$prop_dad,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$prop_dad, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
pcv4 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$propd,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$propd, conf.int=T, method = "kendall")
pcv5 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$propi,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$propi, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
pcv6 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$propr,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$propr, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
pcv7 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$propq,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$propq, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
pcv8 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$props,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$props, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
pcv9 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$propn,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$propn, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
pcv10 <- cor.test(subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="06"& subj!="17")$type_token_ratio,
subset(sixseven_basiclevel_home_data_agg, audio_video=="video" & month=="07"& subj!="17")$type_token_ratio, conf.int=T, method = "kendall")
## Warning in cor.test.default(subset(sixseven_basiclevel_home_data_agg,
## audio_video == : Cannot compute exact p-value with ties
pcv_ps <- cbind(pcv1$p.value,pcv2$p.value,pcv3$p.value, pcv4$p.value, pcv5$p.value, pcv6$p.value, pcv7$p.value, pcv8$p.value, pcv9$p.value, pcv10$p.value)
round(p.adjust(pcv_ps, method = "holm"),3)#prop_mom, prop_dad,
## [1] 0.713 0.000 0.000 0.293 0.069 0.713 0.713 0.713 0.713 0.713
round(pcv_ps,3)
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## [1,] 0.662 0 0 0.042 0.009 0.14 0.25 0.226 0.119 0.161
table(pcv_ps<.05)
##
## FALSE TRUE
## 6 4
table(p.adjust(pcv_ps, method = "holm")<.05)
##
## FALSE TRUE
## 8 2
pcv2 %>% tidy()
## estimate statistic p.value method
## 1 0.4429467 4.071858 4.663969e-05 Kendall's rank correlation tau
## alternative
## 1 two.sided
pcv3 %>% tidy()
## estimate statistic p.value method
## 1 0.6292412 4.811621 1.497114e-06 Kendall's rank correlation tau
## alternative
## 1 two.sided
pca_ps <- cbind(pca1$p.value,pca2$p.value,pca3$p.value, pca4$p.value, pca5$p.value, pca6$p.value, pca7$p.value, pca8$p.value, pca9$p.value, pca10$p.value)
round(p.adjust(pca_ps, method = "holm"),3)# 2,3,4,5,6,8,10: all but propop, propq, and propn
## [1] 0.487 0.017 0.007 0.007 0.000 0.007 0.216 0.017 0.060 0.000
round(pca_ps, 3)
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## [1,] 0.487 0.004 0.001 0.001 0 0.001 0.108 0.003 0.02 0
table(pca_ps<.05)
##
## FALSE TRUE
## 2 8
table(p.adjust(pca_ps, method = "holm")<.05)
##
## FALSE TRUE
## 3 7
#removing 1 7 and 9 bc ns
pca_taus <- cbind(pca2$estimate,pca3$estimate, pca4$estimate, pca5$estimate, pca6$estimate, pca8$estimate, pca10$estimate)
range(pca_taus)
## [1] 0.2959831 0.4608879
pwv_ps <- cbind(pwv1$p.value,pwv2$p.value,pwv3$p.value, pwv4$p.value, pwv5$p.value, pwv6$p.value, pwv7$p.value, pwv8$p.value, pwv9$p.value, pwv10$p.value)
round(p.adjust(pwv_ps, method = "holm"),3)
## [1] 1.000 1.000 0.535 1.000 1.000 1.000 0.535 0.161 1.000 1.000
round(pwv_ps, 3)
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## [1,] 0.948 0.223 0.059 0.611 0.395 0.641 0.063 0.016 0.223 0.832
table(pwv_ps<.05)
##
## FALSE TRUE
## 9 1
table(p.adjust(pwv_ps, method = "holm")<.05)
##
## FALSE
## 10
# none of them differ
pwa_ps <- cbind(pwa1$p.value,pwa2$p.value,pwa3$p.value, pwa4$p.value, pwa5$p.value, pwa6$p.value, pwa7$p.value, pwa8$p.value, pwa9$p.value, pwa10$p.value)
round(p.adjust(pwa_ps, method = "holm"),3)
## [1] 1 1 1 1 1 1 1 1 1 1
round(pwa_ps, 3)
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## [1,] 0.575 0.234 0.767 0.448 0.138 0.964 0.583 0.429 0.913 1
table(pwa_ps<.05)
##
## FALSE
## 10
table(p.adjust(pwa_ps, method = "holm")<.05)
##
## FALSE
## 10
#most six props aren't different
propwsix1 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="06"& subj!="17"), prop_op~audio_video, conf.int=T, paired = T)
propwsix2 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="06"& subj!="17"), prop_mom~audio_video, conf.int=T, paired = T)
propwsix3 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="06"& subj!="17"), prop_dad~audio_video, conf.int=T, paired = T)
## Warning in wilcox.test.default(x = c(0.202272727272727,
## 0.0790378006872852, : cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(x = c(0.202272727272727,
## 0.0790378006872852, : cannot compute exact confidence interval with zeroes
propwsix4 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="06"& subj!="17"), propd~audio_video, conf.int=T, paired = T)
propwsix5 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="06"& subj!="17"), propi~audio_video, conf.int=T, paired = T)
propwsix6 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="06"& subj!="17"), propr~audio_video, conf.int=T, paired = T)
## Warning in wilcox.test.default(x = c(0.152272727272727,
## 0.132875143184422, : cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(x = c(0.152272727272727,
## 0.132875143184422, : cannot compute exact confidence interval with zeroes
propwsix7 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="06"& subj!="17"), propq~audio_video, conf.int=T, paired = T)
propwsix8 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="06"& subj!="17"), props~audio_video, conf.int=T, paired = T)
## Warning in wilcox.test.default(x = c(0.0636363636363636,
## 0.0469644902634593, : cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(x = c(0.0636363636363636,
## 0.0469644902634593, : cannot compute exact confidence interval with zeroes
propwsix9 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="06"& subj!="17"), propn~audio_video, conf.int=T, paired = T)
propwsix10 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="06"& subj!="17"), type_token_ratio~audio_video, conf.int=T, paired = T)
## Warning in wilcox.test.default(x = c(0.284090909090909,
## 0.297823596792669, : cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(x = c(0.284090909090909,
## 0.297823596792669, : cannot compute exact confidence interval with zeroes
propwsix_ps <- cbind(propwsix1$p.value,propwsix2$p.value,propwsix3$p.value, propwsix4$p.value, propwsix5$p.value, propwsix6$p.value, propwsix7$p.value, propwsix8$p.value, propwsix9$p.value, propwsix10$p.value)
round(p.adjust(propwsix_ps, method = "holm"),3) #1, 4,7, 10: prop_op, propd, propq, and ttr
## [1] 0.017 0.122 0.122 0.005 0.599 0.941 0.000 0.463 0.463 0.001
round(propwsix_ps, 3)
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## [1,] 0.002 0.02 0.021 0.001 0.3 0.941 0 0.127 0.116 0
table(propwsix_ps<.05)
##
## FALSE TRUE
## 4 6
table(p.adjust(propwsix_ps, method = "holm")<.05)
##
## FALSE TRUE
## 6 4
#most six props aren't different
propwseven1 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="07"), prop_op~audio_video, conf.int=T, paired = T)
propwseven2 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="07"), prop_mom~audio_video, conf.int=T, paired = T)
propwseven3 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="07"), prop_dad~audio_video, conf.int=T, paired = T)
## Warning in wilcox.test.default(x = c(0.366541353383459,
## 0.00403768506056528, : cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(x = c(0.366541353383459,
## 0.00403768506056528, : cannot compute exact confidence interval with zeroes
propwseven4 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="07"), propd~audio_video, conf.int=T, paired = T)
propwseven5 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="07"), propi~audio_video, conf.int=T, paired = T)
propwseven6 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="07"), propr~audio_video, conf.int=T, paired = T)
## Warning in wilcox.test.default(x = c(0, 0.106325706594886,
## 0.192393736017897, : cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(x = c(0, 0.106325706594886,
## 0.192393736017897, : cannot compute exact confidence interval with zeroes
propwseven7 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="07"), propq~audio_video, conf.int=T, paired = T)
propwseven8 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="07"), props~audio_video, conf.int=T, paired = T)
## Warning in wilcox.test.default(x = c(0.172932330827068,
## 0.122476446837147, : cannot compute exact p-value with zeroes
## Warning in wilcox.test.default(x = c(0.172932330827068,
## 0.122476446837147, : cannot compute exact confidence interval with zeroes
propwseven9 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="07"), propn~audio_video, conf.int=T, paired = T)
propwseven10 <- wilcox.test(data = subset(sixseven_basiclevel_home_data_agg, month=="07"), type_token_ratio~audio_video, conf.int=T, paired = T)
propwseven_ps <- cbind(propwseven1$p.value,propwseven2$p.value,propwseven3$p.value, propwseven4$p.value, propwseven5$p.value, propwseven6$p.value, propwseven7$p.value, propwseven8$p.value, propwseven9$p.value, propwseven10$p.value)
round(p.adjust(propwseven_ps, method = "holm"),3) #1, 2,3,4,7,10: prop_op, prop_mom, prop_dad, propd, propq, and ttr
## [1] 0.035 0.007 0.014 0.000 0.503 1.000 0.035 1.000 1.000 0.000
round(propwseven_ps, 3)
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## [1,] 0.007 0.001 0.002 0 0.126 0.338 0.006 0.368 0.977 0
table(propwseven_ps<.05)
##
## FALSE TRUE
## 4 6
table(p.adjust(propwseven_ps, method = "holm")<.05)
##
## FALSE TRUE
## 4 6
propwseven_estdiff <- cbind(propwseven1$estimate,propwseven2$estimate,propwseven3$estimate, propwseven4$estimate, propwseven5$estimate, propwseven6$estimate, propwseven7$estimate, propwseven8$estimate, propwseven9$estimate, propwseven10$estimate)
range((propwseven_estdiff))
## [1] -0.16398422 0.09655242
median(propwseven_estdiff)
## [1] -0.01813784
#only propi is correlated at 6 months, audio to video
propcsix1 <- cor.test(data=subset(sixseven_spreadAV, month=="06"& subj!="17"), ~v_prop_op+a_prop_op,conf.int=T, method = "kendall")
propcsix2 <- cor.test(data=subset(sixseven_spreadAV, month=="06"& subj!="17"), ~v_prop_mom+a_prop_mom,conf.int=T, method = "kendall")
## Warning in cor.test.default(x = c(0.933333333333333, 0.96551724137931,
## 0.981481481481482, : Cannot compute exact p-value with ties
propcsix3 <- cor.test(data=subset(sixseven_spreadAV, month=="06"& subj!="17"), ~v_prop_dad+a_prop_dad,conf.int=T, method = "kendall")
## Warning in cor.test.default(x = c(0.0583333333333333, 0, 0, 0,
## 0.0315789473684211, : Cannot compute exact p-value with ties
propcsix4 <- cor.test(data=subset(sixseven_spreadAV, month=="06"& subj!="17"), ~v_propd+a_propd,conf.int=T, method = "kendall")
propcsix5 <- cor.test(data=subset(sixseven_spreadAV, month=="06"& subj!="17"), ~v_propi+a_propi,conf.int=T, method = "kendall")
## Warning in cor.test.default(x = c(0.00833333333333333,
## 0.0172413793103448, : Cannot compute exact p-value with ties
propcsix6 <- cor.test(data=subset(sixseven_spreadAV, month=="06"& subj!="17"), ~v_propr+a_propr,conf.int=T, method = "kendall")
## Warning in cor.test.default(x = c(0.241666666666667, 0, 0, 0,
## 0.0842105263157895, : Cannot compute exact p-value with ties
propcsix7 <- cor.test(data=subset(sixseven_spreadAV, month=="06"& subj!="17"), ~v_propq+a_propq,conf.int=T, method = "kendall")
## Warning in cor.test.default(x = c(0.233333333333333, 0.448275862068966, :
## Cannot compute exact p-value with ties
propcsix8 <- cor.test(data=subset(sixseven_spreadAV, month=="06"& subj!="17"), ~v_props+a_props,conf.int=T, method = "kendall")
## Warning in cor.test.default(x = c(0.0166666666666667, 0,
## 0.111111111111111, : Cannot compute exact p-value with ties
propcsix9 <- cor.test(data=subset(sixseven_spreadAV, month=="06"& subj!="17"), ~v_propn+a_propn,conf.int=T, method = "kendall")
propcsix10 <- cor.test(data=subset(sixseven_spreadAV, month=="06"& subj!="17"), ~v_type_token_ratio+a_type_token_ratio,conf.int=T, method = "kendall")
propcsix_ps <- cbind(propcsix1$p.value,propcsix2$p.value,propcsix3$p.value, propcsix4$p.value, propcsix5$p.value, propcsix6$p.value, propcsix7$p.value, propcsix8$p.value, propcsix9$p.value, propcsix10$p.value)
round(p.adjust(propcsix_ps, method = "holm"),3) #only propi
## [1] 0.554 0.211 0.554 1.000 0.039 0.834 1.000 0.554 0.547 1.000
round(propcsix_ps, 3)
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## [1,] 0.082 0.023 0.079 0.359 0.004 0.209 0.691 0.094 0.068 0.492
table(propcsix_ps<.05)
##
## FALSE TRUE
## 8 2
table(p.adjust(propcsix_ps, method = "holm")<.05)
##
## FALSE TRUE
## 9 1
propcsix5
##
## Kendall's rank correlation tau
##
## data: v_propi and a_propi
## z = 2.889, p-value = 0.003864
## alternative hypothesis: true tau is not equal to 0
## sample estimates:
## tau
## 0.3061568
#most seven props are correlated
propcseven1 <- cor.test(data=subset(sixseven_spreadAV, month=="07"), ~v_prop_op+a_prop_op,conf.int=T, method = "kendall")
propcseven2 <- cor.test(data=subset(sixseven_spreadAV, month=="07"), ~v_prop_mom+a_prop_mom,conf.int=T, method = "kendall")
## Warning in cor.test.default(x = c(0.973684210526316, 1,
## 0.940298507462687, : Cannot compute exact p-value with ties
propcseven3 <- cor.test(data=subset(sixseven_spreadAV, month=="07"), ~v_prop_dad+a_prop_dad,conf.int=T, method = "kendall")
## Warning in cor.test.default(x = c(0, 0, 0, 0, 0.045, 0.0103092783505155, :
## Cannot compute exact p-value with ties
propcseven4 <- cor.test(data=subset(sixseven_spreadAV, month=="07"), ~v_propd+a_propd,conf.int=T, method = "kendall")
propcseven5 <- cor.test(data=subset(sixseven_spreadAV, month=="07"), ~v_propi+a_propi,conf.int=T, method = "kendall")
## Warning in cor.test.default(x = c(0.0175438596491228, 0.0612244897959184, :
## Cannot compute exact p-value with ties
propcseven6 <- cor.test(data=subset(sixseven_spreadAV, month=="07"), ~v_propr+a_propr,conf.int=T, method = "kendall")
## Warning in cor.test.default(x = c(0, 0, 0.111940298507463, 0, 0.25, 0, 0, :
## Cannot compute exact p-value with ties
propcseven7 <- cor.test(data=subset(sixseven_spreadAV, month=="07"), ~v_propq+a_propq,conf.int=T, method = "kendall")
propcseven8 <- cor.test(data=subset(sixseven_spreadAV, month=="07"), ~v_props+a_props,conf.int=T, method = "kendall")
## Warning in cor.test.default(x = c(0.596491228070175, 0, 0,
## 0.808510638297872, : Cannot compute exact p-value with ties
propcseven9 <- cor.test(data=subset(sixseven_spreadAV, month=="07"), ~v_propn+a_propn,conf.int=T, method = "kendall")
## Warning in cor.test.default(x = c(0, 0, 0.156716417910448,
## 0.0567375886524823, : Cannot compute exact p-value with ties
propcseven10 <- cor.test(data=subset(sixseven_spreadAV, month=="07"), ~v_type_token_ratio+a_type_token_ratio,conf.int=T, method = "kendall")
## Warning in cor.test.default(x = c(0.271929824561404, 0.489795918367347, :
## Cannot compute exact p-value with ties
propcseven_ps <- cbind(propcseven1$p.value,propcseven2$p.value,propcseven3$p.value, propcseven4$p.value, propcseven5$p.value, propcseven6$p.value, propcseven7$p.value, propcseven8$p.value, propcseven9$p.value, propcseven10$p.value)
round(p.adjust(propcseven_ps, method = "holm"),3) #2,3,4,6: propmom, propdad, propd, propr
## [1] 0.740 0.037 0.037 0.035 0.094 0.037 0.175 0.740 0.651 0.094
round(propcseven_ps, 3)
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## [1,] 0.37 0.004 0.005 0.004 0.016 0.004 0.044 0.42 0.217 0.016
table(propcseven_ps<.05)
##
## FALSE TRUE
## 3 7
table(p.adjust(propcseven_ps, method = "holm")<.05)
##
## FALSE TRUE
## 6 4
propcseven_taus <- cbind(propcseven2$estimate,propcseven3$estimate, propcseven4$estimate, propcseven6$estimate)
range(propcseven_taus)
## [1] 0.3023256 0.3338215
#are things different by month graph, paired wilcoxon
ggplot(sixseven_basiclevel_home_data_agg, aes(month, r))+ geom_line(aes(group = subj))+
stat_summary(fun.y=mean, geom="line",aes(group=1), color = "red", size=2)+
stat_summary(fun.data=mean_cl_boot, aes(group=1), color = "red")+
facet_wrap(~audio_video, scales = "free")

ggplot(sixseven_spreadAV, aes(v_r, a_r))+
geom_point()+
stat_smooth()+
facet_wrap(~month)
## `geom_smooth()` using method = 'loess'

ggplot(sixseven_spreadmonth, aes(six_r, sev_r))+
geom_point()+
stat_smooth(method = "rlm")+
facet_wrap(~audio_video)
## Warning: Computation failed in `stat_smooth()`:
## object 'rlm' of mode 'function' was not found
## Warning: Computation failed in `stat_smooth()`:
## object 'rlm' of mode 'function' was not found

# propvals_med <- sixseven_basiclevel_home_data_agg %>%
# dplyr::select(month, audio_video, prop_op, prop_mom, prop_dad, propd, propi, propn, propq, propr, props, type_token_ratio) %>%
# group_by(month, audio_video) %>%
# #summarise_if(is.numeric, funs(min, max, mean, median))
# summarise_if(is.numeric, funs(median)) %>%
# gather(prop_meas, medianval, prop_op:type_token_ratio)
#
# propvals_mean <- sixseven_basiclevel_home_data_agg %>%
# dplyr::select(month, audio_video, prop_op, prop_mom, prop_dad, propd, propi, propn, propq, propr, props, type_token_ratio) %>%
# group_by(month, audio_video) %>%
# #summarise_if(is.numeric, funs(min, max, mean, median))
# summarise_if(is.numeric, funs(mean)) %>%
# gather(prop_meas, meanval, prop_op:type_token_ratio)
propvals_long <- sixseven_basiclevel_home_data_agg %>%
dplyr::select(month, audio_video, subj, prop_op, prop_mom, prop_dad, propd, propi, propn, propq, propr, props, type_token_ratio) %>%
group_by(month, audio_video, subj) %>%
gather(prop_meas, propval, prop_op:type_token_ratio)
countvals_long <- sixseven_basiclevel_home_data_agg %>%
dplyr::select(month, audio_video, subj, y_op, MOT, FAT, d, i, n, q, r, s, numtypes, numtokens, numspeakers) %>%
group_by(month, audio_video, subj) %>%
gather(count_meas, countval, y_op:numspeakers)
# ggplot(propvals_med, aes(fill = prop_meas, linetype=audio_video,prop_meas, medianval))+
# facet_wrap(month~audio_video,ncol=1)+geom_bar(stat="identity", color = "black")
# ggplot(propvals_med, aes(fill = prop_meas, linetype=audio_video, month, medianval))+
# geom_bar(stat="identity", color = "black", position ="dodge")
# ggplot(propvals_mean, aes(fill = prop_meas, linetype=audio_video, month, meanval))+
# geom_bar(stat="identity", color = "black", position ="dodge")
ggplot(propvals_long, aes(fill = prop_meas, linetype =audio_video, month, propval))+
stat_summary(fun.y=mean, geom="bar", position = "dodge", aes(linetype=audio_video), color = "black")+
stat_summary(fun.data=mean_cl_boot, geom="pointrange", position=position_dodge(width=.9),
aes(group = interaction(prop_meas,month,audio_video)))

ggplot(countvals_long, aes(fill = count_meas, linetype =audio_video, month, countval))+
stat_summary(fun.y=mean, geom="bar", position = "dodge", aes(linetype=audio_video), color = "black")+
stat_summary(fun.data=mean_cl_boot, geom="pointrange", position=position_dodge(width=.9),
aes(group = interaction(count_meas,month,audio_video)))+
facet_wrap(count_meas~audio_video, scales="free_y", nrow=6)
